The AI Trap: Chasing Tech Without the ROI Final

Industrial AI implementation requires shifting from broad, vague automation goals to targeted, high-ROI use cases that solve specific frontline operational challenges. Willem Sundblad, CEO of Oden Technologies, emphasizes that successful digital transformation hinges on data quality and the ability to provide actionable, real-time recommendations to operators. Because modern AI models are probabilistic rather than deterministic, organizations must prioritize data labeling to bridge the gap between raw system data and tribal knowledge. Rather than attempting to automate entire processes, firms achieve the best results by using AI to augment human workflows and eliminate performance variability between shifts. Ultimately, leadership must treat AI initiatives like a venture capital portfolio, rapidly scaling successful, data-rich experiments while maintaining a "human-in-the-loop" approach to ensure trust and adoption on the factory floor.